overhead required to find a given unit of data. In order to find a given unit of data, the big
data environment has to search through a whole host of data. Many input/output
operations (I/Os) have got to be done to find a given item. To find that same item in a
structured DBMS environment, only a few I/Os need to be done. So if you want to
optimize on the speed of access of data, the standard structured DBMS is the way to go.
On the other hand, in order to achieve the speed of access, an elaborate infrastructure for
data is required by the standard structured DBMS. An infrastructure must be both built
and maintained over time, as data change. A considerable amount of system resources is
required for the building and maintenance of this infrastructure. But when it comes to big
data, the infrastructure required to be built and maintained is nil. The big data
infrastructure is built easily and maintained very easily.
This section began with the proposition that repetitive data can be found in both the
structured and big data environment. At first glance, the repetitive data are the same or
are very similar. But when you look at the infrastructure and the mechanics implied in the
infrastructure, it is seen that the repetitive data in each of the environments are indeed
very different.
Chapter 1.2: The Data Infrastructure